154516

A Proposed Approach for Production in ERP Systems Using Support Vector Machine Algorithm

Article

Last updated: 03 Jan 2025

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Abstract

Using machine learning in Enterprise Resource and Planning system, enable the organization to store, manage and analyze their data to get the right decisions and gain valued visions that were previously unimaginable. One of the most usages of machine learning in Enterprise Resource and Planning is forecasting. There are many industries and lines of business that contain large volumes of data such as manufacturing, finance, healthcare…etc. This paper introduces a proposed approach to how to use machine learning in the production module in Enterprise Resource and Planning systems. This approach is considered a novel attempt to enable Enterprise Resource and Planning system to make an automatic or semi-automatic decision in critical issues in manufacturing. The proposed approach is used for recommending a new combination of product raw materials using machine learning. It reduces the cost, time, and efforts to produce a new product design that will help the organization to improve its profitability.

DOI

10.21608/ijicis.2021.60741.1057

Keywords

Machine Learning, ERP, Materials discovery, Production Forecasting

Authors

First Name

Hassan

Last Name

ElMadany

MiddleName

-

Affiliation

Ph.D. student at Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

Email

hassanelmadany@cis.asu.edu.eg

City

Cairo

Orcid

0000-0002-7605-2398

First Name

Marco

Last Name

Alfonse

MiddleName

-

Affiliation

Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

Email

marco_alfonse@cis.asu.edu.eg

City

cairo

Orcid

0000-0003-0722-3218

First Name

Mostafa

Last Name

Aref

MiddleName

-

Affiliation

Computer Science Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, Egypt

Email

mostafa.aref@cis.asu.edu.eg

City

cairo

Orcid

0000-0002-1278-0070

Volume

21

Article Issue

1

Related Issue

21725

Issue Date

2021-02-01

Receive Date

2021-01-31

Publish Date

2021-02-01

Page Start

49

Page End

58

Print ISSN

1687-109X

Online ISSN

2535-1710

Link

https://ijicis.journals.ekb.eg/article_154516.html

Detail API

https://ijicis.journals.ekb.eg/service?article_code=154516

Order

4

Type

Original Article

Type Code

494

Publication Type

Journal

Publication Title

International Journal of Intelligent Computing and Information Sciences

Publication Link

https://ijicis.journals.ekb.eg/

MainTitle

A Proposed Approach for Production in ERP Systems Using Support Vector Machine Algorithm

Details

Type

Article

Created At

22 Jan 2023